考虑二维装箱约束的多车场带时间窗的车辆路径问题模型及算法研究

发布时间：2018-04-27 15:59

本文选题：车辆路径问题 + 二维装箱问题　；参考：《中国管理科学》2017年07期

【摘要】：研究包含时间窗、多车场因素的二维装箱车辆路径问题,建立相应的数学模型,并提出求解该问题的一种新的混合算法,混合算法由量子粒子群算法和引导式局部搜索算法组成。其中,量子粒子群算法用于求解车辆路径问题,引导式局部搜索算法用于求解可行装箱方案。在引导式局部搜索算法中,提出一种基于最小浪费原则的启发式装箱规则,以灵活确定待装货物和装货空间之间的匹配关系,减少重复确定装箱方案所消耗的时间。设计了两组数值试验:第一组基于标准算例库,并将混合算法计算结果与已有文献中的结果进行对比;第二组基于随机生成的新算例,新算例给出多车场和时间窗数据,用于演示混合算法对新模型的计算过程和计算结果。两组数值试验的结果表明,混合算法在效率和性能方面均有较好的表现,计算结果和计算时间均优于已有文献,且混合算法能够较好的求解包含时间窗、多车场因素的二维装箱车辆路径问题模型。
[Abstract]:In this paper, the two-dimensional packing vehicle routing problem with time windows and multi-yard factors is studied, the corresponding mathematical model is established, and a new hybrid algorithm is proposed to solve the problem. The hybrid algorithm consists of quantum particle swarm optimization (QPSO) and guided local search algorithm. Quantum Particle Swarm Optimization (QPSO) is used to solve the vehicle routing problem and the guided local search algorithm is used to solve the feasible packing scheme. In the guided local search algorithm, a heuristic packing rule based on the principle of minimum waste is proposed to flexibly determine the matching relationship between the loading space and the goods to be loaded, and to reduce the time taken to determine the packing scheme repeatedly. Two groups of numerical experiments are designed: the first group is based on the standard example library, and the results of the hybrid algorithm are compared with the results in the existing literatures, and the second group is based on the random generation of new examples, the new example gives the multi-field and time window data. It is used to demonstrate the calculation process and results of the hybrid algorithm for the new model. The results of two groups of numerical experiments show that the hybrid algorithm has better performance in efficiency and performance, and the computational results and computation time are better than those in previous literatures, and the hybrid algorithm can solve the inclusion time window better. A two-dimensional packing vehicle routing problem model with multi-yard factors.
【作者单位】：北京信息科技大学;北京科技大学;
【基金】：国家自然科学基金青年项目(71602008) 北京市社会科学基金研究基地项目(16JDGLC032) 北京交通大学人才基金(B15RC00150)
【分类号】：O224;TP18

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